Hasil untuk "Biochemistry"

T. Mino, M. Loosdrecht, J. Heijnen

T. Mann

R. Thauer

P. J. Davies

J. Harborne

A. Sonenshein, J. Hoch, R. Losick

R. Schwartzman, J. Cidlowski

G. Kroemer, P. Petit, N. Zamzami et al.

A. Coppen

R. Murray...

E. Cadenas

G. Baird, D. Zacharias, R. Tsien

P. E. Van den Steen, B. Dubois, I. Nelissen et al.

Elisabeth Huff Lonergan, Wangang Zhang, S. Lonergan

O. Kabil, R. Banerjee

H2S, the most recently discovered gasotransmitter, might in fact be the evolutionary matriarch of this family, being both ancient and highly reduced. Disruption of γ-cystathionase in mice leads to cardiovascular dysfunction and marked hypertension, suggesting a key role for this enzyme in H2S production in the vasculature. However, patients with inherited deficiency in γ-cystathionase apparently do not present vascular pathology. A mitochondrial pathway disposes sulfide and couples it to oxidative phosphorylation while also exposing cytochrome c oxidase to this metabolic poison. This report focuses on the biochemistry of H2S biogenesis and clearance, on the molecular mechanisms of its action, and on its varied biological effects.

G. Blomquist, A. Bagnères

C. Masters, D. Selkoe

Guoyao Wu

Sara Walker, Estelle Janin, Evgenya Shkolnik et al.

This white paper introduces a framework for applying Assembly Theory (AT) to planetary atmospheres as a biosignature framework suitable for the Habitable Worlds Observatory (HWO). AT quantifies the minimum combinatorial complexity required to co-construct an observed ensemble of molecular species, providing a measure of how much selection and evolution is encoded in a planetary atmosphere's chemical space, without assuming any specific biochemistry, kinetics nor metabolism. We outline some forthcoming results applying this framework and how it can be extended to population-level exoplanet studies, validated against existing spectroscopic data, and used to directly inform HWO instrumental requirements. Rather than imposing a binary alive/dead classification, AT-based atmospheric analysis would provide a continuous measure of planetary complexity, opening a path toward detecting life-as-we-don't-know-it.

Daniele Cappelletti, Giulio Cuniberti, Paola Siri

Stochastic reaction networks are mathematical models with a wide range of applications in biochemistry, ecology, and epidemiology, and are often complex to analyze. Except for some special cases, it is generally difficult to predict how the abundances of all considered species evolve over time. A possible approach to address this issue is to develop tools to compare the model under study with a similar one whose behavior is better understood. The main contribution of our work is to provide direct and computable conditions that can be used to ensure the existence of an ordered coupling between two stochastic reaction networks and to identify which parameter changes in a given model lead to an increase or decrease in the count of certain species. We also make available an algorithm that implements our theory, and we illustrate it with several applications.